The antaresProcessing package

François Guillem

2018-11-28

The antaresProcessing package provides functions that uses data created with package antaresRead to compute standard aggregate like customer surplus or sector surplus. This document demonstrates how to use the main functions of the package.

Installation

The antaresProcessing package can be installed from zip file. Its installation requires that the antaresRead package has already been installed. If it is not already the case, you can use the following commands.

Basic usage

The usage of the package is quite straightforward. First one has to read data from an antares study with readAntares and then pass it to a function of antaresProcessing. Each function requires different type of data (areas, links…) and different level of detail. Generally, functions that perform non-linear calculations require hourly data for each Monte-Carlo scenario but they have arguments to then aggregate the results at the desired level of detail. On the contrary, functions that do linear calculations accept every level of detail and their output has the same level of detail as their input.

The following table sums up the required data and the output of the different functions. For more details, one can look at the help file of each function. Especially, each help page contains an example that minimizes the amount of data read.

Function

Description

requires

time step

works on synthesis

surplus

Consumer and producer surplus

areas, links

hourly

no

surplusClusters

Surplus of clusters

clusters, areas

hourly

no

surplusSectors

Surplus of sectors of production

areas, clusters

hourly

no

addNetLoad

Net load

areas and/or districts

all

yes

netLoadRamp

Ramp of net load

areas and/or districts

hourly

no

margins

Downward and upward margins of an area

areas, clusters

all

yes

modulation

modulation of cluster units or sectors

areas or districts or clusters

all

yes

There is also a compare function that can be used to compare two tables with same shape. It is useful to compare the results of two simulations.